Modern communication systems support deployments wherein single-source terminals are configured to communicate various types of information to multiple terminals. One example of such a deployment includes a cellular communication system, such as a universal mobile telecommunication system (UMTS), wherein a base station communicates with a plurality of user terminals. Another example deployment includes an access point transmitting to multiple terminals in a wireless local area network (WLAN) system. These single-source-to-multiple-terminal types of deployments are commonly referred to as “broadcasting”, “multicasting”, or more generally as “point-to-multipoint” (PtM) communications.
Traditional PtM communication systems may be classified into one of two categories. The first category includes deployments in which transmissions to various receivers are permitted to interfere with each other. An example of this first type of PtM deployment includes a traditional code division multiple-access (CDMA) system, wherein pseudo-random codes are used to code various communications prior to their transmission. Upon receiving the coded transmissions, the user terminals synchronize the codes of the various transmissions to recover the communicated data. Although pseudo-random coding in the transmission source is useful in mitigating cross-interference, the true burden of mitigating this interference lies in the receiving terminals.
In the second, more frequently utilized category of PtM deployments, interference is altogether avoided via the use of orthogonal transmissions. Examples of such deployments include those specified by the Global System for Mobile Communications (GSM) standards, such as frequency division multiple access (FDMA) systems and time division multiple access (TDMA) systems. In these types of PtM communication systems, a transmitting terminal transmits various communication signals using mathematically orthogonal or non-interfering “spaces”. These spaces may be defined as a frequency range (as in a FDMA system), a time-slot (as in a TDMA system), or a Walsh code (as in an orthogonal code CDMA system). Unlike the first category of PtM communication systems, the transmitting terminal in this second category is solely responsible for preventing signal interference. As a result, receiving terminals in such systems are typically no more complex than those used in basic point-to-point communication systems. Although this category of PtM systems is superior, it should be understood that the performance of such systems is limited by the number of available orthogonal spaces and/or dimensions.
Referring now to FIG. 1, a graph 100 illustrating achievable data transmission rates 101-105 to the two receivers, Rx A and Rx B, in a PtM system is shown. It should be understood that FIG. 1 is for illustrative purposes only and that is does not represent actual test results.
If all the available transmission bandwidth in a FIG. 1 system were allocated to say, receiver Rx A, Rx A would receive service at a highest achievable data rate C1 and Rx B would receive no data. Similarly, if all the available transmission bandwidth were allocated to receiver Rx B, Rx B would receive service at a highest achievable data rate C2 and Rx A would receive no data.
If receivers Rx A and Rx B were operating in, for example, a TDMA system (which is equivalent to time-sharing), they would be capable of achieving data transmission rates at and to the left of the solid line 101 on the graph 100. As time sharing represents a special case of orthogonal multiplexing, similar rates are achievable by any system which maintains orthogonality between transmission signals.
In a PtM system, where orthogonality between transmission signals is not maintained, the transmission performance to any number of receivers can suffer as compared to that of an orthogonal system, such as TDMA. To illustrate, reference is again made to FIG. 1. Line 102, for example, may be representative of achievable data rates in a typical random code CDMA system utilizing a standard RAKE receiver. Line 103 may be representative of achievable data rates in a typical random code CDMA system utilizing a more advanced MMSE multi-user detector. As indicated by the graph 100, the achievable data rates represented by line 103 are superior to those represented by line 102. Neither provides, however, the performance of line 101, which as described above, represents an achievable performance rate of transmission signals that are maintained orthogonal to each other.
It is well known from information theory that data rates superior to that of orthogonal coding (e.g., TDMA) are achievable in PtM systems. These superior data rates may be represented, for example, by lines 104 and 105 of the graph 100 shown in FIG. 1. To achieve these superior data rates 104, 105, however, requires the use of receivers having receiver structures that are far more advanced then those used in typical receivers. To illustrate, information-theoretic successive interference cancellation (IT-SIC) can improve the performance of a CDMA system to where it actually performs better than TDMA systems. While such a result is counterintuitive at first, it is noted that the performance of a TDMA system is limited by the availability of orthogonal or non-interfering spaces or time-slots. IT-SIC structures allow interference, but in a controlled manner, and shifts interference cancellation to the receivers. Utilizing such structures enables a CDMA system to achieve data rates beyond those achievable with TDMA systems, such as those represented by the line 104 on the graph in FIG. 1.
There are several problems with this IT-SIC approach. First, it requires highly complex receivers. Providing such complex receivers is problematic particularly in modern cellular systems, wherein the receivers must be able to be embedded in relatively small, inexpensive terminal units with limited battery life. In addition, these complex receivers must possess information regarding both their own communication channel and the communication channels of all other users in the system. Dissemination of such channel information in practical communication systems is highly challenging.
The problems cited above may be addressed using a technique called dirty paper coding (DPC). It is known theoretically that DPC performs at least as well as IT-SIC and in many cases, optimizes data throughput as illustrated by dashed line 105 on the graph 100 in FIG. 1. In addition to providing for superior system performance, DPC has the added benefit of being a transmit-side (“pre-coding”) technique. In other words, as in traditional TDMA and FDMA systems, the burden and complexity of interference cancellation is dealt with in the transmitting terminal, but without the limitations of orthogonal spaces. As a result, receivers are only required to possess detailed information pertaining to their particular communications. Furthermore, because each receiver operates optimally without possessing details of transmissions intended for other receivers, DPC provides a methodology for hiding transmissions from unintended receivers, thus making it suitable to support data hiding, watermarking, and other security applications.
The term “precoding”, as used herein, refers to the mutual coding of multiple data streams while in the transmitter in order to pre-cancel any interference the data streams may cause each other; as opposed to attempting to cancel interference at individual receiving terminals post-transmission. It should be understood that pre-coding does not specifically imply that further coding steps will be performed, although further coding functions are possible.
While recent analysis of DPC has yielded significant progress in the theoretical understanding of this technique, little is understood about how to build practical communication systems with DPC.
Accordingly, it is desirable to have a method and apparatus that utilizes DPC to optimize system performance and improve the signal quality of transmission signals. It is further desirable to have a method and apparatus that utilizes DPC to support security-oriented applications such as data-hiding and watermarking.
It is well known that the use of multiple antennas provides for increased data throughput (via multiplexing) and improved signal quality of transmission signals (via diversity and/or beamforming). In addition, multiple antenna implementations, such as those found in MIMO (Multiple-Input Multiple-Output) and/or Smart antenna systems, enable transmission signals to be separated in a spatial domain (e.g., Spatial Division Multiple Access). To exploit these multiple antenna advantages, a MIMO technique, for example, may be combined with a signal processing technique such as FEC (forward error correction) coding and/or a radio air interface such as CDMA. There does not exist, however, a means for further improving multiple antenna systems utilizing DPC.
Accordingly, it is further desirable to have a method and apparatus that combines DPC with multiple antenna implementation(s) to improve both system performance and security enhancements.